Machine learning approaches to sentiment analytics

One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train th...

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Main Authors: ZHAO, W., SIAU, Keng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/9410
https://ink.library.smu.edu.sg/context/sis_research/article/10410/viewcontent/Machine_Learning_Approaches_to_Sentiment_Analytics.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-104102024-10-25T08:44:12Z Machine learning approaches to sentiment analytics ZHAO, W. SIAU, Keng One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, genders were separated and two separate machines were used to learn the emotions of the two genders. We also manipulated the training sample sizes and study the effect of training sample sizes on the two machine learning approaches. Our preliminary results show that the approach where the genders were separated produces a higher accuracy in classifying emotions. We also observe that training sample sizes have different impact on the two approaches. 2017-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/9410 https://ink.library.smu.edu.sg/context/sis_research/article/10410/viewcontent/Machine_Learning_Approaches_to_Sentiment_Analytics.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Sentiment Analytics Emotion classification Machine Learning Artificial Intelligence and Robotics Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Sentiment Analytics
Emotion classification
Machine Learning
Artificial Intelligence and Robotics
Databases and Information Systems
spellingShingle Sentiment Analytics
Emotion classification
Machine Learning
Artificial Intelligence and Robotics
Databases and Information Systems
ZHAO, W.
SIAU, Keng
Machine learning approaches to sentiment analytics
description One key aspect of sentiment analytics is emotion classification. This research studies the use of machine learning approaches to classify human emotion. Two different machine learning approaches were compared in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, genders were separated and two separate machines were used to learn the emotions of the two genders. We also manipulated the training sample sizes and study the effect of training sample sizes on the two machine learning approaches. Our preliminary results show that the approach where the genders were separated produces a higher accuracy in classifying emotions. We also observe that training sample sizes have different impact on the two approaches.
format text
author ZHAO, W.
SIAU, Keng
author_facet ZHAO, W.
SIAU, Keng
author_sort ZHAO, W.
title Machine learning approaches to sentiment analytics
title_short Machine learning approaches to sentiment analytics
title_full Machine learning approaches to sentiment analytics
title_fullStr Machine learning approaches to sentiment analytics
title_full_unstemmed Machine learning approaches to sentiment analytics
title_sort machine learning approaches to sentiment analytics
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/sis_research/9410
https://ink.library.smu.edu.sg/context/sis_research/article/10410/viewcontent/Machine_Learning_Approaches_to_Sentiment_Analytics.pdf
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